Vorasidenib
My tumor has IDH1 R132C. That is why IDH inhibition matters here. Vorasidenib is FDA-approved for grade 2 astrocytoma or oligodendroglioma with a susceptible IDH1 or IDH2 mutation after surgery, and it is the IDH inhibitor I am on now.
My cancer, explained visually
I sequenced my own tumor. Here is what it is made of.
The mutations that define it are IDH1, ATRX, and TP53. A peptide pipeline took 314,801 candidates down to 18. This page walks through all of it in plain language, and where a number came from, I say so.
The plan, in two moves
Hit the mutation with an approved drug, then try to make the tumor visible to my immune system
What I am trying to do is go after the tumor in two different ways: use an FDA-approved IDH inhibitor for the mutation that defines my cancer, and explore a personalized vaccine that tries to make selected tumor mutations visible to my immune system. This is my treatment story, not proof that the vaccine, or the combination, improves outcomes.
Personal neoantigen vaccine
The vaccine is built from my tumor's own mutations, so it only exists for me. Nobody knows yet whether it helps, and nobody knows whether pairing it with the IDH drug helps — both are still experiments. It's made of peptides that cross the mutated spots, the idea being to point my T cells at fragments of protein that shouldn't be in a healthy body.
IDH1 R132C tumor biology
IDH pathway inhibition with vorasidenib
Personal neoantigen vaccine
Exploratory idea
Why this feels different to me: it isn't a drug, then a vaccine, in sequence. It's two mechanisms
at once — quiet the mutant IDH enzyme and drop its 2-HG output, while separately teaching the immune
system to spot a handful of tumor-specific peptides. That second half, and running both together, is
still unproven.
Data portal
Where to start
This isn't a tidy conclusion. It's the case laid open: what got measured, what I computed myself, what's public on this page, and what you'd have to email me for.
Timeline
The clinical story
Diagnosis, surgery, surveillance, treatment starts, vaccine milestones, and the life around all of it.
OverviewThe numbers I track
Diagnosis, IDH inhibitor context, somatic calls, peptide funnel counts, TMB/MSI, purity, and PGx coverage.
Vaccine funnelFrom mutations to peptides
How my tumor mutations became a computational peptide list, then a smaller vaccine-design shortlist.
Variant atlasMy tumor findings
IDH1, ATRX, TP53 / Li-Fraumeni context, MGMT methylation, HLA type, and vaccine-relevant peptides.
Raw accessAsk for source data
Raw genome, tumor VCF, peptide-level files, and source reports need privacy boundaries and version notes.
Data
The numbers
Some of these come straight off my medical reports. Others are first-pass counts from code I wrote to make sense of the raw files. I've marked which is which.
Diagnosis
From my recordWhat the tumor isAstrocytoma, IDH-mutant, CNS WHO grade 2right frontal lobe
Why vorasidenib mattersVorasidenibFDA-approved IDH inhibitor for grade 2 IDH-mutant glioma after surgery
Genomics
From my recordComputed analysisSomatic calls649618 genes with somatic evidence
Canonical drivers425 other genes flagged for review
TMB / MSI1.5 mut/Mb / MSSearlier TMB estimates varied by assay/reporting method
Tumor purity32%purity estimate used by the run
PGx core-site call rate80%how much of the PGx core set was covered
Vaccine funnel
Computed analysisPeptides screened314,801a big first-pass computational list, not clinical candidates
Predicted strong HLA binders2,104peptides predicted to bind strongly
Vaccine-design shortlist18prioritized long-peptide design candidates
Personal neoantigen vaccine
How my personalized vaccine candidates were picked
I worked with a pipeline that starts with mutations in my tumor and narrows them down to peptides most likely to be visible to my immune system. Those peptides then become the starting point for a personalized vaccine.
Computed analysis
Clinical benefit unknown
Find mutations that are present in the cancer and different from normal tissue.
Look for mutation-spanning peptides that could be shown by my HLA molecules.
Use selected peptides as patient-specific vaccine material.
The goal is for immune cells to recognize selected pieces of the tumor.
Start with my tumor
Start with tumor sequencing and look for mutation-spanning peptides that should look different from normal self.
Personalized vaccine
CeGAT's vaccine is personalized rather than off-the-shelf: the input is my tumor's molecular profile.
T-cell recognition goal
The point is to help T cells recognize a patient-specific tumor profile, using peptides selected from the tumor's own mutations.
Variant explorer
The variants themselves
These are the findings that actually matter — the drivers, the immune-presentation details, the peptides — pulled from my Tempus, BostonGene, and pathology reports. Click any one to see what it means and how confident I am about it.
From my record
Computed analysis
Donate
Support brain cancer research
If this story makes you want to help, these are established places to support brain tumor research, patient programs, and translational work.
National nonprofit
American Brain Tumor Association
Research funding, patient education, and support for people facing brain tumors.
National advocacyNational Brain Tumor Society
Research, policy work, and patient-centered advocacy across brain tumor types.
Academic centerUCSF Brain Tumor Center
Clinical and translational brain tumor research at UCSF.
Translational researchIvy Brain Tumor Center
Early-phase research and trials focused on brain tumor treatment.
Research nonprofitGlioblastoma Foundation
Research support focused on glioblastoma and aggressive brain tumors.
Research foundationSontag Foundation
Funding and programs for brain cancer research and early-career investigators.
Part 2 of 4 · The biology
Understanding one tumor led to a bigger question: could the same work help someone else?
The next chapter is the tool that grew out of this analysis, with the doctor kept firmly in the loop.